The concept of Artificial Intelligence has been around for centuries. At its very root, AI is the concept of using technology, or a group of technologies, to enable machines to sense, understand, act and learn to supplement human activity.

AI was first mostly a fixture in science-fiction novels, and later became a reality with the introduction of the Turing Machine in the early 1940s. Since then, AI has evolved in shorts and stops: with the stops happening in the “AI winters” of late 1970s and the late 1980s which temporarily suspended AI research and exploration, primarily due to lack of government interest and finances.

But, by the mid-90’s, with the advance of robotics, the concept of a self-reasoning being to deal with real-world problems began to take shape again. And, with each passing year, researchers and scientists integrated a number of mathematical and logical concepts such as probability, decision theory, neural networks and evolutionary algorithms into AI, making it capable of solving problems across various fields: from banking software, medical diagnostic tools, speech recognition software, internet search engines, and even marketing automation.

The Age of AI and Big Data

In this age of Big Data and Social Media, with the pervasive availability of large amounts of real-time data from multiple sources in various forms, artificial intelligence marketing has evolved to the point where we can develop tools that are able to capitalize on ideation and user-generated content. This advancement has widely opposing impacts on traditional businesses which primarily depend on capital investments and labor, and on IPOs centered on innovations based in ideation and UGC, like Facebook, Twitter and Snapchat.

The primary takeaway is that the time is ripe for businesses to integrate AI and Math Marketing into their processes and products since it has the ability to provide them with new sources of growth, positively impact their labor, and improve the experience of the people who drive their business: the consumers.

survey conducted by Accenture revealed that by 2035, AI has the potential to increase productivity by 40% or more. The study also revealed that the potential for increased labor efficiency in developed economies will be driven primarily by innovations and advances in AI that are aimed at enabling consumers to use their time and effort more efficiently.

Also Read Using and Understanding Big Data to Optimize Your Online Strategy

The Wide-Reaching Benefits of AI

By integrating AI into their processes, businesses can drive growth in the following three channels:

1. Intelligent Automation

AI has ushered businesses into an age of Intelligent Automation, which can drive growth beyond the capabilities of traditional automation solutions. Intelligent automation doesn’t just refer to a mere transfer of tasks from man to machine; it’s about developing automated solutions that are highly sophisticated, flexible, efficient and secure, and that provide the most value to a business and drive growth exponentially. In essence, these are solutions with the capabilities to:

  • Adapt easily and flexibly to the complexity of tasks to complete them efficiently
  • Work seamlessly across multiple industries and roles
  • Self-learn complex tasks

2. Labor and Capital Augmentation

AI allows businesses to use their labor and capital assets efficiently. It allows humans to focus mainly on adding value to their work; that is, it lets them imagine, create and innovate while it handles the execution of low-value tasks that would otherwise take time and effort and bring down overall efficiency. AI augments labor by complementing human capabilities, cutting down time and costs. AI also helps businesses maximize the use of their assets, allowing them to invest their capital efficiently.

3. Diffusion of Innovation

This refers to the propulsion of innovation throughout the economy: when one sector of the economy is driven by automation, its innovations automatically extend to other sectors owing to the inter-dependability of each of these sectors through ripple effect.

For example, with the advent of driverless cars, automotive giants like Ford and BMW have partnered up with Silicon Valley giants like Google, MIT and Stanford University to develop AI-driven vehicles. However, the effect of automation in driving extends beyond the automotive industry, such as:

  • Since driverless cars remove the drivers need to concentrate on driving, it frees them up for leisure activities like browsing the internet: something that mobile advertisers and retailers can capitalize on.
  • Insurance agencies can capitalize on the data generated by driverless cars to develop new policies that cover mobility, and not just driving.
  • The traffic and road data generated by driverless cars can be used to supplement artificial intelligence, therefore, has the potential to generate new revenue streams within an economy, and thereby increases profitability across multiple sectors.

The Effect of AI on Industry Growth in the Economy

According to Accenture’s Study, they estimated that AI had the potential of boosting profitability in the economy by at least 38% with a Gross Value of US $14 Trillion added by the end of 2035. In particular, the study revealed that:

  • AI had the potential to boost industry growth, particularly in the sectors of communication, manufacture and finance.
  • There was a potential for unprecedented profitability, particularly in the manufacturing sector owing to the increased efficiency and productivity offered by AI over manual and faulty equipment.

How We Can Prepare For a Future in AI

 There are opposing views on the implications of advances in AI: while some entrepreneurs like Elon Musk warn against the existential and ethical crises that increased dependence on AI could create, others view it as a solution to some of the world’s greatest challenges.

Therefore, the key to integrating AI into our future lies in understanding the complexities of both the positive and negative implications, and preparing to address the challenges they present.

Prepare the future generation for AI

At present, technology education is primarily one-way: humans learn to use technology. With the advent of AI, humans and machines will need to co-exist in a two-way dependency. This will necessitate a change in the type of knowledge and skill-sets imparted to future generations.

Technical skills will need to expand to include the ability to design and develop AI systems including specialization skills in robotics, haptics, audio-visuals, and pattern recognition. At the same time, interpersonal skills, creativity and emotional intelligence will become more important.

Encourage AI-powered regulation

To keep with the pace of technological advance, current regulations need to be updated to become more adaptive to the use of increased automation.

For instance, in the medical industry, AI can have a huge impact in diagnosing health issues. However, physicians may be leery of depending on an AI diagnosis for fear of being sued for malpractice due to a technical error. Therefore, the regulations pertaining to medical malpractice need to be revisited and updated.

Enforce a code of ethics in regards to AI

As AI becomes more integrated, its societal and ethical implications need to be addressed, as well. For instance, in autonomous vehicles, whose life should the car choose to save: its own driver or the other drivers? Or, how does one deal with racially biased algorithms?

To further the prevalence of AI in a society primarily guided by human behaviors and biases, a code of ethics needs to be put in place by policy-makers. Strict rules surrounding the common standards and best-practices for the development of AI technology need to be established.

Address the Effects in the Workplace

The fear of being replaced by machines and losing primary sources of income has been steadily on the rise since the dawn of the Industrial Revolution. With the advent of AI, that fear is only becoming more pervasive. Therefore, advocates of AI need to understand that these concerns are valid, and seek ways to address them effectively.

They need to do this by focusing on the benefits of AI: increasing individual efficiency in the workplace and improving job satisfaction. They also need to highlight and clearly articulate the broader impact of AI in solving world problems like climate change through reduced dependence on fuel and quicker access to health care.

At the same time, AI policy makers also need to create contingency plans to reintegrate work-groups that will be seriously impacted by automation back into the economy.

Conclusion

Artificial intelligence is here to stay: its impact on both social and economic advancements is apparent. Since it allows for increased productivity and efficiency, it boosts the innovative and creative capabilities of a business.

At the same time, however, there are a number of legal, ethical and social implications that need to be addressed before we can fully integrate AI into our future.